• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2016, Volume: 9, Issue: 19, Pages: 1-6

Original Article

Revealing Hidden Profile Information and Ranking Job Seekers on Big Data


Objectives: This paper presents a system to list out the description of vacancies by having seen the internal relationship between the information provided by the job seekers profile and job providers requirement. So, all right candidates get all right jobs. Methods/Analysis: The information provided by the job seekers profile and job providers’ requirement in the job portal which is not revealed after the Keyword Matching Process (KMP) alone. After the KMP the process called expert analysis is involved here to reveal them out. So, the missing of any job information to the right candidate is avoided. Further this analysis also ranking the job seekers based on two criteria. Firstly, fresher: based on mark percentage and skills. Secondly, experienced: based on years of experience. Findings: After the KMP and expert analysis processes the hidden information’s are revealed and by the process of ranking job provider’s recruitment process are made easy by replying only to the top ranking candidates such that for fresher the top rank goes to high percentage candidates and for experienced the top rank goes to the high years of experience candidate for their recruitment process. And there is an added advantage of gender classification. So, the job seekers need not apply for other gender’s job and the job providers also get the replies only from their needed gender criterion alone. Novelty /Improvement: This paper made an easy approach of finding the jobs for job seekers and job seekers for job providers and the added advantage of ranking the job seekers, gender classification.

Keywords: Expert Analysis, Internal Relationship, Job Seekers, Job Providers, Job Portal, Keyword Matching Process


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